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Updated: Sep 16, 2025

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Multi-Area, Multi-Service and Multi-Tier Edge-Cloud Continuum Planning.

Anargyros J Roumeliotis1, Efstratios Myritzis1, Evangelos Kosmatos1

  • 1Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, GR-157 80 Athens, Greece.

Sensors (Basel, Switzerland)
|July 12, 2025
PubMed
Summary
This summary is machine-generated.

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Optimal planning for edge-cloud environments involves deploying compute continuum resources efficiently. Batch-based task processing offers a faster, scalable solution for complex computing needs.

Area of Science:

  • Computer Science
  • Distributed Systems
  • Edge Computing

Background:

  • Edge-cloud environments are increasingly complex, requiring efficient resource management.
  • Optimal planning is crucial for meeting diverse processing, rate, and latency demands.
  • Existing offline planning methods may struggle with real-world problem sizes.

Purpose of the Study:

  • To investigate optimal planning strategies for multi-area, multi-service, multi-tier edge-cloud systems.
  • To evaluate different approaches for deploying the compute continuum (processing devices and their allocation).
  • To analyze the trade-offs between performance and execution time for various planning schemes.

Main Methods:

  • Comparison of three offline compute continuum planning schemes: one processing all tasks at once, and two using iterative task batching.
Keywords:
artificial intelligenceedge computinginferencemultiple areas and services and tiersoptimization

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  • Analysis of direct complex versus simpler, faster planning methods.
  • Investigation of task selection strategies, including random selection and clustering methods, for group-based approaches.

    • Main Results:

    • Processing all tasks simultaneously offers better performance but incurs longer execution times.
    • Iterative, batch-oriented schemes provide a faster approach and are more scalable for larger problems.
    • Random task selection in group-based schemes generally yields better performance compared to other strategies.

    Conclusions:

    • Batch-oriented compute continuum planning is effective for large-scale edge-cloud environments.
    • The choice of task selection strategy significantly impacts the performance of group-based planning.
    • Random task selection emerges as a robust strategy for optimizing performance in these systems.